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Expasoft - From artificial intelligence to supernatural business results
Our services

Solving customer’s problems we go deep into the issue and client’s specific to deliver maximum added value to our clients by created solutions

Consulting

Developing a customized ML-solutions based on a deep client’s IT-systems, operational processes and data bases analysis

ML-products

Adapting our own ML-products to Client’s business tasks

ML-audit

Quick but detailed clients IT-systems and business goals and risk analysis and developing recommendations for Machine learning integration

Deep technological research

Math problem statement research, state-of-the-art methods research, world leading scientific teams cooperation, developing unique algorithms, proof of concept projects

Data Science education

Extensive practice-oriented course with a useful scientific bases and practical tasks by leaders in applied machine learning data scientists.

Technologies
Big data, Machine learning, Deep Machine learning, Artificial intelligence

Face recognition using video data from specially modernized “smart” camera on board (IoT). High accuracy and precision performance without any “clouds”: no remote server required. Examples of technology facilities and potential tasks: face detection, face recognition, age and gender recognition.

Speaker voice recognition as well as specific incidents identification such as broken glass, gunshots, applause, crying etc. Person identification by voice sample. Examples of technology facilities and potential tasks: automatic summarization, coreference resolution, part-of-speech tagging, named entity recognition, natural language understanding, question answering, sentiment analysis, topic segmentation, topic modeling, acoustic event detection, voice recognition, voice command recognition

Objects recognition such as people, cars, loaders, specific goods on shelves etc. by video data stream or pictures. Examples of technology facilities and potential tasks: face detection, common object detection, tracking of moving objects, object segmentation.

Integration of the learning neural networks into mobile devices with an opportunity to easily train the system for solving business tasks. For example, different types of specific video and audio analytics on board of smartphone.

Smart predictive analytics based on a wide range of different data provides recommendations or make decisions itself with a flexible reaction to the results. Continuous machine learning with an increase in forecasts precisions. Examples of technology facilities and potential tasks: data exploration, building scoring and predictive models, statistical classifiers development, exploring hidden patterns, missing data reconstruction, outliers filtering, collaborative filtering (user based, item based), content-based recommendations, kMeans, Latent Factor Models, Conjoint Analysis, Hybrid Models

  • Video Analytics: ScoreFace
  • Audio Analytics: VoiceBox
  • Computer Vision
  • Embedded Neural Network Technology
  • Machine Learning, Deep Learning
Our team

Our team consists of young and enthusiastic people devoted to machine learning and AI-innovations

Vladimir has over 15 years’ experience in data science and machine learning. He has both scientific and practical business expertise in data science, machine learning and AI.

Vladimir Dyubanov CEO and founder

Anastasia has a deep expertise in public relations, HR and marketing. She has over 7 years’ experience in relations with international clients from different industries.

Anastasia Konakova Chief Commercial officer

Konstantin has MBA degree in corporate strategy and over 10 years’ experience in business consulting in different industries concerning risk management, business development and process optimization.

Konstantin Seleznev Strategy and development director

Eugeny has over 15 years’ practical experience in marketing, innovation and strategic management in different industries: heavy machinery, electronics, IT.

Eugeny Grigoriev Chief marketing officer
Main instruments

Python: Scikit learn, Numpy, Pandas, Revolution R, Azure ML, SPSS Climentine, Knime, Vowpal wabbit, CNN, LSTM, DNN, Café, Theano, Tensor flow, Rule based, Bag of words, TFIDF, Latent semantic analysis, Word2vec, Doc2vec, Spark, Hadoop, MlLib, AWS (Redshift)

Portfolio

Expasoft has over 7 years successful experience in the AI market, over 45 projects for 10 industries: medicine and pharma - 6, banking -3, industrial production -5 , oil&gas- 7, IT - 3, security - 4, retail - 9, media -9, telecom - 5, logistics – 2.

Write-off mistakes identification
Smart HR analytics
People and cars detection – precision 95%
Documents recognition and reading – precision 95%
Computer vision - LookApp
Website view customization
Clients identification by voice sample for lending institution and fraud prevention
Prediction of customers amount in supermarket for every day for the year
Mobile neural networks
Clients and partners

We develop long-term relations with our clients and partners on mutually beneficial bases. We strive to bring maximum benefits and added value to both clients and partners.

Clients
partners
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